%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
T(Theory)
P(Phenomena)
D(Data)
T -- "Explanation" --> P
P -- "Abduction" --> T
P -- "Prediction" --> D
D -- "Generalization" --> P
Buridan’s Ass
2023-09-19
%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
T(Theory)
P(Phenomena)
D(Data)
T -- "Explanation" --> P
P -- "Abduction" --> T
P -- "Prediction" --> D
D -- "Generalization" --> P
See Borsboom et al. (2021). Theory Construction Methodology: A Practical Framework for Building Theories in Psychology. Perspectives on Psychological Science, 16(4), 756–766. https://doi.org/10.1177/1745691620969647
%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
P(Phenomena)
D(Data)
P -- "Prediction" --> D
D -- "Generalization" --> P
Phenomena: Stable and general features of the world in need of explanation. Can be understood as robust generalizations of patterns in empirical data. They are the explanatory targets for scientific theories. In psychology often called “effects” or “findings”.
Data: Relatively direct observations. Refer to particular empirical patterns in concrete data sets rather than empirical generalizations (which would be phenomenona).
See Borsboom et al. (2021). Theory Construction Methodology: A Practical Framework for Building Theories in Psychology. Perspectives on Psychological Science, 16(4), 756–766. https://doi.org/10.1177/1745691620969647
%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
P(Phenomena)
D(Data)
P -- "Prediction" --> D
D -- "Generalization" --> P
linkStyle 1 stroke-width:2px,stroke:red,color:red;
Data provide evidence for the existence of empirical phenomena: You generalize from one or more data sets with strong evidence to a general phenomenon.
Generalize to what? UTOS framework:
To claim a (robust) phenomenon, you ideally need:
UTOS framework from Cronbach & Shapiro (1982); for an update to “M-STOUT”, including mechanims and time, see Findley et al. (2021). External Validity. Annual Review of Political Science, 24(1), 365–393. https://doi.org/10.1146/annurev-polisci-041719-102556
%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
P(Phenomena)
D(Data)
P -- "Prediction" --> D
D -- "Generalization" --> P
linkStyle 1 stroke-width:2px,stroke:red,color:red;
Probably most of psychology is about establishing phenomena (disguised as “theories”).
Techniques used to detect data patterns:
See presentation of Denny Borsboom
%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
P(Phenomena)
D(Data)
P -- "Prediction" --> D
D -- "Generalization" --> P
linkStyle 0 stroke-width:2px,stroke:red,color:red;
Phenomena (once their existence has been established) predict similar data patterns in new data sets of the same operationalization (as in “direct replication”) and ideally also for new operationalizations (as in “conceptual replication”, changing more UTOS dimensions).
The risky shift phenomenon: A group’s decisions are riskier than the average of the individual decisions of members before the group met (i.e., the group discussion made individuals riskier).
See Westfall et al. (2015). Replicating Studies in Which Samples of Participants Respond to Samples of Stimuli. Perspectives on Psychological Science, 10(3), 390–399. https://doi.org/10.1177/1745691614564879
Questions for discussion (10 min.):
My take: It is a phenomenon (though a weak one), as it generalizes to new units (i.e., data sets) of the same operationalization. But the generalizability was much weaker than initially expected. It is a phenomenon of this specific stimulus set (treatment operationalization) and suggests certain types of research questions (e.g., “What is so specific to this stimulus set?”).
%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
P(Phenomena)
D(Data)
P -- "Prediction" --> D
D -- "Generalization" --> P
The concerns of the replication crisis typically referred to the relation between data and phenomena:
%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
T(Theory)
P(?? Phenomena ??)
D(Data)
T -- "Explanation" --> P
P -- "Abduction" --> T
P ---> D
D -. "?? Generalization ??" .-> P
linkStyle 2 stroke-width:0px,stroke:grey,color:grey;
linkStyle 3 stroke-width:2px,stroke:red,color:red;
Doubts about phenomena propagate to theories: If there is no phenomenon to explain, any explanatory theory gets obsolete.
“We argue that a further cause of poor replicability is the often weak logical link between theories and their empirical tests.”
See Oberauer, K., & Lewandowsky, S. (2019). Addressing the theory crisis in psychology. Psychonomic Bulletin & Review, 26(5), 1596–1618. https://doi.org/10.3758/s13423-019-01645-2
Obstacles to building useful theories in psychology:
Slide by Karolin Salmen, CC-BY
See Eronen & Bringmann (2021)
Wenn die Psychologie das Fehlen eines theoretischen Fundaments beklagt, so greift diese Diagnose zu kurz: Woran es ihr eigentlich mangelt, ist ein Nährboden, auf dem ein solches Fundament überhaupt entstehen könnte. Ihr fehlt das große heuristische Narrativ. Die Physik hat ein solches Narrativ; es ist der Glaube an die Sphärenmusik einer kosmischen Harmonie, erkennbar an dem Vertrauen, mit dem man erwartet, auf Symmetrien, Erhaltungssätze und überhaupt auf einfache Zusammenhänge zu stoßen. Die Psychologen haben sich dieses Narrativ ausgeborgt; aber bei ihnen funktioniert es nicht.
Auch für sie aber läge ein solcher Kompass bereit, und die Systemtheorie könnte sie lehren, ihn zu nutzen. Den Technikern ist er seit je vertraut, und ebenso ordnet und lenkt er das Denken der Biologen […]. Dieses heuristische Narrativ - wir werden es in diesem Buch unter dem Stichwort des demiurgischen Prinzips kennenlernen - ist die Vision des kosmischen Ingenieurs, des Weltbaumeisters, der den Organismus unter der Leitidee nicht der Harmonie, sondern der Funktionalität, des “Wozu” konstruiert hat.
See Bischof (2021), “Struktur und Bedeutung”
Formal modeling in psychology - Empirisches Praktikum, Ludwig-Maximilians-Universität München